Bedside ultrasound education in Canadian medical schools: A national survey
Bibliographic record
Abstract
BACKGROUND: This study was carried out to determine the extent and characteristics of bedside ultrasound teaching in medical schools across Canada. METHODS: A cross-sectional, survey-based study was used to assess undergraduate bedside ultrasound education in the 17 accredited medical schools in Canada. The survey, consisting of 19 questions was pilot-tested, web-based, and completed over a period of seven months in 2014. RESULTS: Approximately half of the 13 responding medical schools had integrated bedside ultrasound teaching into their undergraduate curriculum. The most common trends in undergraduate ultrasound teaching related to duration (1-5 hours/year in 50% of schools), format (practical and theoretical in 67% of schools), and logistics (1:4 instructor to student ratio in 67% of schools). The majority of responding vice-deans indicated that bedside ultrasound education should be integrated into the medical school curriculum (77%), and cited a lack of ultrasound machines and infrastructure as barriers to integration. CONCLUSIONS: This study documents the current characteristics of undergraduate ultrasound education in Canada.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".